Journal ArticleDOI
The Problem of Pattern Recognition in Arrays of Interconnected Objects. Statement of the Recognition Problem and Basic Assumptions
TLDR
The prior assumption consisting in the fact that neighboring objects more often belong to one class than to different classes will permit one to improve the recognition quality in comparison with the classical case of the independence of classes of separate objects.Abstract:
In the classical pattern recognition problem, consideration is given to individual objects, each of which actually belongs to one of the finite number of classes and is presented for the recognition irrespective of other objects. Recognition objects often form a single interconnected array determined by the nature of the event involved, namely, its natural extent in time or in space along one or a few coordinates. As a consequence, the need arises to take consistent decisions about the classes for all elements of the array. The prior assumption consisting in the fact that neighboring objects more often belong to one class than to different classes will permit one to improve the recognition quality in comparison with the classical case of the independence of classes of separate objects.read more
Citations
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Journal ArticleDOI
A skeleton features-based fall detection using microsoft kinect v2 with one class-classifier outlier removal
TL;DR: The proposed algorithm is based on the skeleton features encoding on the sequence of neighboring frames and support vector machine classifier, and a version of a cumulative sum method is applied for combining the individual decisions on the consecutive frames.
Journal ArticleDOI
A Problem of Pattern Recognition in Arrays of Interrelated Objects. Recognition Algorithm
TL;DR: The classical methods of pattern recognition theory presuppose the independence of elements of a recognizable set, but in the case of interrelated objects, the decision on the class of each object is taken independent of the decisions on the classes of other objects.
Journal ArticleDOI
Recognition of dependent objects based on acyclic Markov models
TL;DR: The reduced set of interrelations between array elements is balanced by an extended set of acyclic graphs themselves, which are investigated by the example of the segmentation problem for texture raster images and presented.
References
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Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
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